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- W3114371388 abstract "164 Objectives: Radiomics is based on extracting high throughput quantitative features from images in order to better characterize pathophysiological and physiological process. [1, 2]. Normal tissue radoimics has not been well studied. We investigated radiomic signatures of the liver in healthy subjects on 18-FDG-PET, and compared different liver segmentation strategies and their effect on the consistency of quantitative imaging features (QIF). Methods: Whole body 18 FDG-PET images were obtained from 23 healthy (20 women and 3 men; mean age ± SD, 23.65 ± 3.57 y) subjects who were scanned after total body cooling procedure for 90 minutes prior to scan. We applied 3 methods of segmentation on PET/CT: 1)-segmenting the whole liver, 2)- segmenting 3 consecutive slices at the level of porta hepatis on axial plane(3S) 3)-segmenting a 3cm diameter sphere in Right hepatic lobe (PERCIST liver VOI). 82 QIFs were extracted using pyradiomics software (http://pyradiomics.readthedocs.io).[3] The consistency of features amongst different segmentation methods was assessed by the interclass correlation coefficient(ICC). The reproducibility of FDG PET QIFs was compared by one-sided paired Wilcoxon rank test. Upon determining the more reliable segmentation method, we compared consistency of each individual QIF family of that method using Kruskal-Wallis H Test. To elucidate the association between all QIFs to better characterize the radiomic phenotype of normal liver, a heat map analysis with hierarchical clustering on median centered QIFs using complete linkage while using Pearson9s correlation coefficient as the similarity measure.Results: 26 QIFs had high reproducibility (ICC > 0.8) between the QIFs extracted from 3S and whole liver Segmentation, while only 14 QIF showed high reproducibility between the QIFs extracted from the sphere and whole liver segmentation. 3S segmentation had significantly higher reproducibility (ICC=0.57±0.32, p-value≍0.9 X 10-10) compared to Sphere segmentation (ICC=0.29±0.34).Reliability of Gray Level Co-occurrence Matrix (GLCM, ICC=0.77±0.24), Gray Level Size Zone Matrix (GLSZM,ICC= 0.28±0.22), Gray Level Run Length Matrix (GLRLM, 0.51±0.29), Neighbouring Gray Tone Difference Matrix (NGTDM, 0.1±0.05) Gray Level Dependence Matrix (GLDM, 0.49±0.29) intensity values (ICC= 0.79±0.22) extracted from 3S segmentation showed significant difference based on Kruskal-Wallis H Test (p-value ≍ 0.14 X 10 -5 ).11 distinct clusters were identified from QIF extracted from the whole liver. Conclusions: 3S segmentation showed considerable reliability for GLCM and 1st order intensity values and can be considered as a rapid alternative to whole liver segmentation for extracting FDG PET radiomic features. Liver PET radiomic signature in healthy subjects provide us with reference values to compare with liver radiomic phenotypes from different liver pathologies and systemic disorders." @default.
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- W3114371388 date "2018-05-01" @default.
- W3114371388 modified "2023-09-26" @default.
- W3114371388 title "FDG PET Radiomic Signature of Normal Liver and its Reproducibility using different Segmentation Strategies" @default.
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